A large dataset of scientific text reuse in Open-Access publications
Abstract We present the Webis-STEREO-21 dataset, a massive collection of Scientific Text Reuse in Open-access publications. It contains 91 million cases of reused text passages found in 4.2 million unique open-access publications. Cases range from overlap of as few as eight words to near-duplicate p...
| Main Authors: | , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2023-01-01
|
| Series: | Scientific Data |
| Online Access: | https://doi.org/10.1038/s41597-022-01908-z |
| _version_ | 1828051885593985024 |
|---|---|
| author | Lukas Gienapp Wolfgang Kircheis Bjarne Sievers Benno Stein Martin Potthast |
| author_facet | Lukas Gienapp Wolfgang Kircheis Bjarne Sievers Benno Stein Martin Potthast |
| author_sort | Lukas Gienapp |
| collection | DOAJ |
| description | Abstract We present the Webis-STEREO-21 dataset, a massive collection of Scientific Text Reuse in Open-access publications. It contains 91 million cases of reused text passages found in 4.2 million unique open-access publications. Cases range from overlap of as few as eight words to near-duplicate publications and include a variety of reuse types, ranging from boilerplate text to verbatim copying to quotations and paraphrases. Featuring a high coverage of scientific disciplines and varieties of reuse, as well as comprehensive metadata to contextualize each case, our dataset addresses the most salient shortcomings of previous ones on scientific writing. The Webis-STEREO-21 does not indicate if a reuse case is legitimate or not, as its focus is on the general study of text reuse in science, which is legitimate in the vast majority of cases. It allows for tackling a wide range of research questions from different scientific backgrounds, facilitating both qualitative and quantitative analysis of the phenomenon as well as a first-time grounding on the base rate of text reuse in scientific publications. |
| first_indexed | 2024-04-10T19:45:08Z |
| format | Article |
| id | doaj.art-55bfb85d93ea4d038ba94d5c42301b77 |
| institution | Directory Open Access Journal |
| issn | 2052-4463 |
| language | English |
| last_indexed | 2024-04-10T19:45:08Z |
| publishDate | 2023-01-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Data |
| spelling | doaj.art-55bfb85d93ea4d038ba94d5c42301b772023-01-29T12:04:08ZengNature PortfolioScientific Data2052-44632023-01-0110111110.1038/s41597-022-01908-zA large dataset of scientific text reuse in Open-Access publicationsLukas Gienapp0Wolfgang Kircheis1Bjarne Sievers2Benno Stein3Martin Potthast4Text Mining and Retrieval Group, Leipzig UniversityText Mining and Retrieval Group, Leipzig UniversityText Mining and Retrieval Group, Leipzig UniversityWeb Technology and Information Systems Group, Bauhaus-Universität WeimarText Mining and Retrieval Group, Leipzig UniversityAbstract We present the Webis-STEREO-21 dataset, a massive collection of Scientific Text Reuse in Open-access publications. It contains 91 million cases of reused text passages found in 4.2 million unique open-access publications. Cases range from overlap of as few as eight words to near-duplicate publications and include a variety of reuse types, ranging from boilerplate text to verbatim copying to quotations and paraphrases. Featuring a high coverage of scientific disciplines and varieties of reuse, as well as comprehensive metadata to contextualize each case, our dataset addresses the most salient shortcomings of previous ones on scientific writing. The Webis-STEREO-21 does not indicate if a reuse case is legitimate or not, as its focus is on the general study of text reuse in science, which is legitimate in the vast majority of cases. It allows for tackling a wide range of research questions from different scientific backgrounds, facilitating both qualitative and quantitative analysis of the phenomenon as well as a first-time grounding on the base rate of text reuse in scientific publications.https://doi.org/10.1038/s41597-022-01908-z |
| spellingShingle | Lukas Gienapp Wolfgang Kircheis Bjarne Sievers Benno Stein Martin Potthast A large dataset of scientific text reuse in Open-Access publications Scientific Data |
| title | A large dataset of scientific text reuse in Open-Access publications |
| title_full | A large dataset of scientific text reuse in Open-Access publications |
| title_fullStr | A large dataset of scientific text reuse in Open-Access publications |
| title_full_unstemmed | A large dataset of scientific text reuse in Open-Access publications |
| title_short | A large dataset of scientific text reuse in Open-Access publications |
| title_sort | large dataset of scientific text reuse in open access publications |
| url | https://doi.org/10.1038/s41597-022-01908-z |
| work_keys_str_mv | AT lukasgienapp alargedatasetofscientifictextreuseinopenaccesspublications AT wolfgangkircheis alargedatasetofscientifictextreuseinopenaccesspublications AT bjarnesievers alargedatasetofscientifictextreuseinopenaccesspublications AT bennostein alargedatasetofscientifictextreuseinopenaccesspublications AT martinpotthast alargedatasetofscientifictextreuseinopenaccesspublications AT lukasgienapp largedatasetofscientifictextreuseinopenaccesspublications AT wolfgangkircheis largedatasetofscientifictextreuseinopenaccesspublications AT bjarnesievers largedatasetofscientifictextreuseinopenaccesspublications AT bennostein largedatasetofscientifictextreuseinopenaccesspublications AT martinpotthast largedatasetofscientifictextreuseinopenaccesspublications |